[docs] update project information

README.md

@@ -1,3 +1,109 @@
 # ml-food-recommendation
 
-Food Recommendation System using TFRS
+![TensorFlow](https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge&logo=TensorFlow&logoColor=white)
+![Docker](https://img.shields.io/badge/docker-%230db7ed.svg?style=for-the-badge&logo=docker&logoColor=white)
+[![Google Colab](https://img.shields.io/badge/open_in_colab-blue?style=for-the-badge&logo=googlecolab&color=blue&labelColor=525252)](https://colab.research.google.com/github/MamMates/ml-food-recommendation/blob/main/MamMates_Food_Recommendation.ipynb)
+![LICENSE](https://img.shields.io/github/license/MamMates/ml-food-recommendation?style=for-the-badge)
+![Docker Version](https://img.shields.io/docker/v/putuwaw/mammates-food-recommendation/latest?style=for-the-badge)
+![Docker Pulls](https://img.shields.io/docker/pulls/putuwaw/mammates-food-recommendation?style=for-the-badge)
+
+Food Recommendation System using TensorFlow Recommenders (TFRS) and deployed using TensorFlow Serving.
+
+Notebook: [MamMates Food Recommendation](https://colab.research.google.com/github/MamMates/ml-food-recommendation/blob/main/MamMates_Food_Recommendation.ipynb)
+
+Dataset: [Food Recommendation Dataset (Dummy)](https://drive.google.com/drive/folders/1lAXsNMC32tJhOEQvpLHyNFP9VyZAux0O?usp=sharing)
+
+## Features 💡
+
+Using MamMates Food Recommendation, you can get food recommendation based on the given `id_user`.
+
+## Prerequisites 📋
+
+- [TensorFlow](https://www.tensorflow.org/) 2.14.0 or higher
+- [TensorFlow Recommenders](https://www.tensorflow.org/recommenders) 0.7.3 or higher
+- [Docker](https://www.docker.com/) 24.0.7 or higher
+
+## Usage ✨
+
+If you already have Docker installed, you only need to run the following command:
+
+- Pull the image from Docker Hub:
+
+```bash
+docker pull putuwaw/mammates-food-recommendation
+```
+
+- Run the image:
+
+```bash
+docker run -p 8504:8504 --name ml-rec putuwaw/mammates-food-recommendation
+```
+
+- You can check that the model is already running by opening the browser and go to http://localhost:8504/v1/models/food_rec
+
+- To do prediction, you can use the following command:
+
+```bash
+curl -s https://raw.githubusercontent.com/MamMates/ml-food-recommendation/main/example.json | curl -X POST -d @- http://localhost:8504/v1/models/food_rec:predict
+```
+
+- You will get the following response:
+
+```json
+{
+  "predictions": [
+    {
+      "output_1": [
+        1.59945917, 1.14119792, 0.741919041, 0.635785818, 0.532811046,
+        0.467606097, 0.457192838, 0.0975963473, 0.017279733, -0.0865440145
+      ],
+      "output_2": ["13", "14", "12", "2", "18", "20", "11", "10", "7", "9"]
+    }
+  ]
+}
+```
+
+## Development 💻
+
+If you want to develop this model, you can follow the steps below:
+
+- Clone this repository:
+
+```bash
+git clone https://github.com/MamMates/ml-food-recommendation.git
+```
+
+- Update the model by changing the saved model in the [model](model/) folder.
+
+- Build the Docker image:
+
+```bash
+docker build -t mammates-food-recommendation .
+```
+
+- Run the image:
+
+```bash
+docker run -p 8504:8504 --name ml-rec mammates-food-recommendation
+```
+
+- You can check that the model is already running by opening browser and go to http://localhost:8504/v1/models/food_rec
+
+- To do prediction, you can use the following command:
+
+```bash
+curl -d @example.json -X POST http://localhost:8504/v1/models/food_rec:predict
+```
+
+- To stop the container:
+
+```bash
+docker stop ml-rec
+```
+
+> [!NOTE]  
+> If you want to learn more about TensorFlow Serving, you can read the REST API documentation [here](https://www.tensorflow.org/tfx/serving/api_rest).
+
+## License 📝
+
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.